A New Approach in Coal Mine Exploration Using Cosmic Ray Muons

Muon radiography is a technique that uses cosmic ray muons to image the interior of large scale geological structures. The muon absorption in matter is the most important parameter in cosmic ray muon radiography. Cosmic ray muon radiography is similar to X-ray radiography. The main aim in this survey is the simulation of the muon radiography for exploration of mines. So, the production source, tracking, and detection of cosmic ray muons were simulated by MCNPX code. For this purpose, the input data of the source card in MCNPX code were extracted from the muon energy spectrum at sea level. In addition, the other input data such as average density and thickness of layers that were used in this code are the measured data from Pabdana (Kerman, Iran) coal mines. The average thickness and density of these layers in the coal mines are from 2 to 4 m and 1.3 gr/c³, respectively. To increase the spatial resolution, a detector was placed inside the mountain. The results indicated that using this approach, the layers with minimum thickness about 2.5 m can be identified.     

Field experiments to improve the efficacy of gargoor (fish trap) fishery in Kuwait’s waters

Fish traps were investigated to understand the effects of season, bait type, trap size, and trap soak time on catch rates, catch composition, and trap loss rates from March 2004 to September 2005, to improve the performance and management of Kuwait’s gargoor (cage style fish trap) fishery, which used to be the nation’s most important one in terms of value and landings volume. Catch rates were the highest in April/May (5-8 kg/trap haul) and again in December (7 kg/trap haul). Bait type and trap size also affected catch rates and species composition. Of the seven baits tested, the best catch rates, >5 kg/trap haul, occurred with cuttlefish (Sepia pharaonis), but wolf-herring (Chirocentrus dorab) and mullet (Liza klunzingeri) also produced good results (4-5 kg/trap haul). Within the five tested sizes, the two largest-sized traps captured more fish and larger size fish. Analysis of variance (ANOVA) showed significant differences of catch rate among traps with different baits as well as among traps of different sizes. Duncan test further revealed these differences between two specific baits and sizes. Cluster Analysis of species composition showed more differences among different baits than among different trap sizes. Longer soak times did not result in larger catch rates, but increased trap loss. About 10-day soak time resulted in trap loss 7%, while 40-day soak time could result in a loss of around 20%. Consequently, it is recommended that the gargoor be checked every 10 or fewer days. The average overall catch rate during the study period was lower than that of 1980s (4.5 vs. 5.8 kg/trap haul), indicating a possible decline of fish abundance in Kuwait’s waters. It is recommended that the number of gargoor fishing boats and gargoors from each boat should be limited to allow stock rehabilitation.     

Performance comparison between logistic and generalized surplus-production models applied to the Sillago sihama fishery in Pakistan

The catch and effort data of Sillago sihama fishery in Pakistani waters were used to investigate the performance of two closely related stock assessment models: logistic and generalized surplus-production models. Compared with the generalized production model, the logistic model produced more reasonable estimates for parameters such as maximum sustainable yield. The Akaike’s Information Criterion values estimated at 4.265 and -51.152 respectively by the logistic and generalized models. Simulation analyses of the S. sihama fishery showed that the estimated and observed abundance indices for the logistic model were closer than those for the generalized production model. Standardized residuals were distributed closer for logistic model, but exhibited a slightly increasing trend for the generalized model. Statistical outliers were seen in 1989 and 1993 for the logistic model, and in 1981 and 1999 for the generalized model. Simulated results revealed that the logistic estimates were close to the true value for low CVs (coefficients of variation) but widely dispersed for high CVs. In contrast, the generalized model estimates were loose for all CV levels. The estimated production model curve parameter was not reasonable at all the tested levels of white noise. With the increase in white noise R2 for the catch per unit effort decreased. Therefore, we conclude that the logistic model performs more reasonably than the generalized production model.     

Recent Sea Level and Sea Surface Temperature Changes Along the Maldives Coast

Maldives, a South Asian small island nation in the northern part of the Indian Ocean is extremely vulnerable to the impacts of Sea Level Rise (SLR) due to its low altitude from the mean sea level. This artricle attempts to estimate the recent rates of SLR in Maldives during different seasons of the year with the help of existing tidal data recorded in the Maldives coast. Corresponding Sea Surface Temperature (SST) trends, utilizing reliable satellite climatology, have also been obtained. The relationships between the SST and mean sea level have been comprehensively investigated. Results show that recent sea level trends in the Maldives coast are very high. At Male, the capital of the Republic of Maldives, the rising rates of Mean Tidal Level (MTL) are: 8.5, 7.6, and 5.8 mm/year during the postmonsoon (October-December), Premonsoon (March-May) and southwest monsoon (June-September) seasons respectively. At Gan, a station very close to the equator, the increasing rate of MTL is maximum during the period from June to September (which is 6.2 mm/year). These rising trends in MTL along the Maldives coast are certainly alarming for this small developing island nation, which is hardly one meter above the mean sea level. Thus there is a need for careful monitoring of future sea level changes in the Maldives coast. The trends presented are based on the available time-series of MTL for the Maldives coast, which are rather short. These trends need not necessarily reflect the long-term scenario. SST in the Maldives coast has also registered significant increasing trend during the period from June to September. There are large seasonal variations in the SST trends at Gan but SST and MTL trends at Male are consistently increasing during all the seasons and the rising rates are very high. The interannual mode of variation is prominent both in SST as well as MTL. Annual profile of MTL along the Maldives coast is bimodal, having two maxima during April and July. The April Mode is by far the dominant one. The SST appears to be the main factor governing the sea level variations along the Maldives coast. The influence of SST and sea level is more near the equatorial region (i.e., at Gan). There is lag of about two months for the maximum influence of SST on the sea level. The correlation coefficient between the smoothed SST and mean tidal level at Gan with lag of two months is as high as ~ +0.8, which is highly significant. The corresponding correlation coefficients at Male with the lags of one and two months are +0.5 and +0.3, respectively. Thus, the important finding of the present work for the Maldives coast is the dominance of SST factor in sea level variation, especially near the region close to the equator.     

Sea Level Changes Along Bangladesh Coast in Relation to the Southern Oscillation Phenomenon

Interannual variations of sea level along the Bangladesh coast are quite pronounced and often dominate the long-term sea level trends that are taking place. The El Niño/Southern Oscillation (ENSO) induced variation is an important component of interannual mode of variations. The present article deals with the relationship between the sea level variations along the Bangladesh coast and the Southern Oscillation phenomenon. The mean tide level data of monsoon season (June to September) pertaining to Hiron Point (in Sundarbans) and Char Changa (on the mouth of Meghna River) have been analyzed and correlated to the Southern Oscillation Index (SOI). The annual variation of mean tide level in the coastal areas of Bangladesh reveals that the tide level reaches its peak during the monsoon season. The maximum tide level during the calendar year is recorded in August. Thus, it is not surprising that the inundation of the coastal belt of Bangladesh due to the floods is most common during the summer monsoon season, especially from July to September. Therefore, the sea level variations during the monsoon are of paramount importance to Bangladesh. The results of the present study show that both at Hiron Point and Char Changa there is a substantial difference between the mean tide level during the El Niño and La Niña monsoons. The mean tide level at Hiron Point is higher by about 5 cm during August of La Niña years as compared to that during the El Niño years. The difference at Char Changa, which is located at the mouth of Meghna River, is much higher. This is probably due to the increased fresh water discharge into the Meghna River during La Niña years. Thus at the time of crossing of a monsoon depression, the chances of widespread inundation are higher during a La Nin~a year as compared to that during an El Niño year. The Correlation Coefficients (CCs) between Mean Tide Levels (MTLs) at Hiron Point and Char Changa and the SOI during September (at the end of monsoon) are +0.33 and +0.39 respectively. These CCs are statistically significant at 90% and 95% levels, respectively. These results may find applications in the preparedness programs for combating sea level associated disasters in Bangladesh.